Grammar Bias and Initialisation in Grammar Based Genetic Programming

Preferential language biases which are introduced when using Tree-Adjoining Grammars in Grammatical Evolution affect the distribution of generated derivation structures, and as such, present difficulties when designing initialisation methods. Similar initial populations allow for a fairer comparison between different GP methods. This work proposes methods for dealing with these biases and examines their effect on performance over four well known benchmark problems. In addition, a comparison is performed with a previous study that did not employ similar phenotype distributions in their initial populations. It is found that the use of this form of initialisation has a positive effect on performance.